Fisher Transform
Converts inputs to a nearly Gaussian probability distribution, creating sharp peaks at turning points.
Usage
Apply to normalized prices or oscillators to sharpen turning-point signals. The near-Gaussian output makes extreme values statistically significant and easy to trade.
Background
Ehlers introduces the Fisher Transform in Cybernetic Analysis (2004) to convert any bounded indicator into a Gaussian normal distribution. Values beyond ±1.5 signal statistically significant price extremes, sharper than raw oscillators.
Formula
\[
Fish(x) = 0.5 \times \ln\left(\frac{1 + x}{1 - x}\right) = \text{atanh}(x)
\]